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Found 23 papers, 13 papers with code
UniKER: A Unified Framework for Combining Embedding and Definite Horn Rule Reasoning for Knowledge Graph Inference
Knowledge graph inference has been studied extensively due to its wide applications.
Comprehensive Assessment of Jailbreak Attacks Against LLMs
Some jailbreak prompt datasets, available from the Internet, can also achieve high attack success rates on many LLMs, such as ChatGLM3, GPT-3. 5, and PaLM2.
IDOL: Indicator-oriented Logic Pre-training for Logical Reasoning
IDOL achieves state-of-the-art performance on ReClor and LogiQA, the two most representative benchmarks in logical reasoning MRC, and is proven to be capable of generalizing to different pre-trained models and other types of MRC benchmarks like RACE and SQuAD 2. 0 while keeping competitive general language understanding ability through testing on tasks in GLUE.
Ranked #1 on
Reading Comprehension
on ReClor
Efficient and Effective Text Encoding for Chinese LLaMA and Alpaca
While several large language models, such as LLaMA, have been open-sourced by the community, these predominantly focus on English corpora, limiting their usefulness for other languages.
MiniRBT: A Two-stage Distilled Small Chinese Pre-trained Model
In natural language processing, pre-trained language models have become essential infrastructures.
From Visual Prompt Learning to Zero-Shot Transfer: Mapping Is All You Need
In this sense, we propose SeMap, a more effective mapping using the semantic alignment between the pre-trained model's knowledge and the downstream task.
Gradient-based Intra-attention Pruning on Pre-trained Language Models
In this work, we propose a structured pruning method GRAIN (Gradient-based Intra-attention pruning), which performs task-specific pruning with knowledge distillation and yields highly effective models.
Data Poisoning Attacks Against Multimodal Encoders
Extensive evaluations on different datasets and model architectures show that all three attacks can achieve significant attack performance while maintaining model utility in both visual and linguistic modalities.
HIT at SemEval-2022 Task 2: Pre-trained Language Model for Idioms Detection
The same multi-word expressions may have different meanings in different sentences.
HFL at SemEval-2022 Task 8: A Linguistics-inspired Regression Model with Data Augmentation for Multilingual News Similarity
This paper describes our system designed for SemEval-2022 Task 8: Multilingual News Article Similarity.
TextPruner: A Model Pruning Toolkit for Pre-Trained Language Models
Pre-trained language models have been prevailed in natural language processing and become the backbones of many NLP tasks, but the demands for computational resources have limited their applications.
PERT: Pre-training BERT with Permuted Language Model
We permute a proportion of the input text, and the training objective is to predict the position of the original token.
Ranked #4 on
Stock Market Prediction
on Astock
CINO: A Chinese Minority Pre-trained Language Model
It covers Standard Chinese, Yue Chinese, and six other ethnic minority languages.
Cross-Lingual Text Classification with Multilingual Distillation and Zero-Shot-Aware Training
In this paper, we aim to improve the multilingual model's supervised and zero-shot performance simultaneously only with the resources from supervised languages.
Adversarial Training for Machine Reading Comprehension with Virtual Embeddings
Adversarial training (AT) as a regularization method has proved its effectiveness on various tasks.
Bilingual Alignment Pre-Training for Zero-Shot Cross-Lingual Transfer
Multilingual pre-trained models have achieved remarkable performance on cross-lingual transfer learning.
Benchmarking Robustness of Machine Reading Comprehension Models
To fill this important gap, we construct AdvRACE (Adversarial RACE), a new model-agnostic benchmark for evaluating the robustness of MRC models under four different types of adversarial attacks, including our novel distractor extraction and generation attacks.
A Sentence Cloze Dataset for Chinese Machine Reading Comprehension
To add diversity in this area, in this paper, we propose a new task called Sentence Cloze-style Machine Reading Comprehension (SC-MRC).
TextBrewer: An Open-Source Knowledge Distillation Toolkit for Natural Language Processing
In this paper, we introduce TextBrewer, an open-source knowledge distillation toolkit designed for natural language processing.
Poisson Kernel Avoiding Self-Smoothing in Graph Convolutional Networks
Graph convolutional network (GCN) is now an effective tool to deal with non-Euclidean data, such as social networks in social behavior analysis, molecular structure analysis in the field of chemistry, and skeleton-based action recognition.
Improving Machine Reading Comprehension via Adversarial Training
With virtual adversarial training (VAT), we explore the possibility of improving the RC models with semi-supervised learning and prove that examples from a different task are also beneficial.
Ekar: An Explainable Method for Knowledge Aware Recommendation
Recently, a variety of methods have been developed for this problem, which generally try to learn effective representations of users and items and then match items to users according to their representations.
Ranked #1 on
Recommendation Systems
on Last.FM
Pre-Training with Whole Word Masking for Chinese BERT
To demonstrate the effectiveness of these models, we create a series of Chinese pre-trained language models as our baselines, including BERT, RoBERTa, ELECTRA, RBT, etc.
